ArticleInternational journal of forecasting
Short-term forecasting of the coronavirus pandemic.
Article in International journal of forecasting. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Analytical reference framework to analyze non-COVID-19 events.Population health metrics · 2023Article
- Do more stringent policies reduce daily COVID-19 case counts? Evidence from Canadian provinces.Economic analysis and policy · 2023Article
- Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study.European journal of operational research · 2023Article
- Forecasting Future Monthly Patient Volume using Deep Learning and Statistical Models.Wireless personal communications · 2023Article
- Chimeric forecasting: combining probabilistic predictions from computational models and human judgment.BMC infectious diseases · 2022Article
- Modeling the COVID-19 epidemic in Croatia: a comparison of three analytic approaches.Croatian medical journal · 2022Article
- Tracking machine learning models for pandemic scenarios: a systematic review of machine learning models that predict local and global evolution of pandemics.Network modeling and analysis in health informatics and bioinformatics · 2022Review
- Modeling and forecasting the COVID-19 pandemic time-series data.Social science quarterly · 2021Article
- The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control: the value and limitations of early models.Proceedings. Biological sciences · 2021Article
- Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology.Scientific reports · 2021Article
- Short-term Covid-19 forecast for latecomers.International journal of forecastingArticle
- COVID-19: Forecasting confirmed cases and deaths with a simple time series model.International journal of forecastingArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have been publishing real-time forecasts of confirmed cases and deaths from coronavirus disease 2019 (COVID-19) since mid-March 2020 (published at www.doornik.com/COVID-19). These forecasts are short-term statistical extrapolations of past and current data. They assume that the underlying trend is informative regarding short-term developments but without requiring other assumptions about how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is spreading, or whether preventative policies are effective. Thus, they are complementary to the forecasts obtained from epidemiological models. The forecasts are based on extracting trends from windows of data using machine learning and then computing the forecasts by applying some constraints to the flexible extracted trend. These methods have been applied previously to various other time series data and they performed well. They have also proved effective in the COVID-19 setting where they provided better forecasts than some epidemiological models in the earlier stages of the pandemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.